PCM is well known for processing of digital signals and operations of digital systems. Differential PCM (DPCM) is also well known to decrease distortion of signal quantification and reduce code capacity of digital encoding. Further, adaptive DPCM (ADPCM) is also well known to improve efficiency and quality of signal processing by dynamically adjusting the quantification scale depending on the signal variations. FIG. 1 shows a system block diagram to illustrate a typical ADPCM encoder arrangement in which a quantizer 10 quantizes the prediction error Ue from an input u subtracting a prediction u to be a quantized prediction error Que and an encoder 12 encodes the quantized prediction error Que to be a code signal c. The quantized prediction error Que and the prediction û are added to be a quantized signal Qu for the input of the predictor 14 to produce the prediction û. The code signal c from the encoder 12 is sent to channel/memory 20. The quantizer 10, predictor 14 and encoder 12 form a DPCM encoder arrangement. An ADPCM encoder arrangement further comprises a delta adaptor 16 and a predictor adaptor 18 to regulate the step size of quantification. By monitoring the code signal c, the delta adaptor 16 produces a step size adaptive signal s for the quantizer 10 and encoder 12. On the other hand, the predictor adaptor 18 produces a predictor factor α by monitoring the quantized signal Qu for the predictor 14 adaptive to various situations. FIG. 2 is a system block diagram of a conventional ADPCM decoding arrangement, in which the code signal c′ received at receiver is connected to a decoder 22 and a delta adaptor 24 to produce a step size adaptive signal s for the decoder 22. The quantized prediction error Que decoded by the decoder 22 is added with a prediction û from a predictor 26 to be a quantized signal Qu. The quantized signal Qu is connected to the predictor 26 to produce the prediction û, and a predictor adaptor 28 produces a predictor factor α by monitoring the prediction û for the predictor 26. A resolution modulator is further incorporated into a DPCM or ADPCM system in Taiwanese Pat. Issued No. 453408 to adjust the encoding resolution based on the output s of the step size adaptor and the quantized prediction error Que.
However, these prior arts only consider the quality of the processed signal itself or the code signal after encoding/decoding, i.e., simply have thought of the variations of signals, without considering other assisted resource. For example, the encoded code is usually buffered by memory before decoding, so that the buffer ability to input signal flow variations will effect the entire performance of the system. Generally, better signal quality could be obtained with longer code length, but it will worsen the response ability of a system to signal variations. For example, when using a CD-ROM drive, if it keeps longer code length or better signal quality, the music or video will be interrupted once the input signal flow of the buffer memory decreased or interrupted by vibration. The larger code capacity is stored in buffer memory, the more variations of input flow can be absorbed. Therefore, the variations of code capacity should be taken into considerations to improve the system performance.